Age related morphological variation of the maxilla: a 3-dimensional (3D) geometric morphometrics analysis

Abstract

Age estimation is a critical component of human identification in forensic context. Recent advances in three-dimensional imaging and shape analysis have enabled the assessment of subtle age-related craniofacial variations beyond traditional methods. This study aimed to evaluate age-related maxillary shape variation using a geometric morphometrics (GM) approach based on three-dimensional head and neck computed tomography (CT) scans. A total of 413 adult CT scans with equal distribution of sex and representing three major ethnic groups (Malay, Chinese and Indian) were analysed and categorised into four age groups: 18–30, 31–40, 41–50, and 51–65 years. A total of 45 3D anatomical landmarks were placed on the maxillary bone. The landmarks were analysed using Procrustes ANOVA, canonical variate Analysis (CVA), discriminant function analysis (DFA). Finally, shape variations were visualised using IDAV landmark editor. Procrustes ANOVA showed a statistically significant difference in the maxillary bone shape across different age groups (p < 0.001). CVA revealed observable shape differentiation between age groups along the canonical variate axes, while DFA achieved classification accuracies ranging from 70.8% to 78.4% in age group discrimination. There were significant variations in terms of the maxillary bone shape across different age groups with acceptable accuracy values. This population-specific data could be applied as forensic reference that tailored to Malaysian population.